def testPickle(self): numVertices = 10 graph = HIVGraph(numVertices) graph[0, 0] = 1 graph[3, 5] = 0.1 output = pickle.dumps(graph) newGraph = pickle.loads(output) graph[2, 2] = 1 self.assertEquals(newGraph[0, 0], 1) self.assertEquals(newGraph[3, 5], 0.1) self.assertEquals(newGraph[2, 2], 0.0) self.assertEquals(newGraph.getNumEdges(), 2) self.assertEquals(newGraph.getNumVertices(), numVertices) self.assertEquals(newGraph.isUndirected(), True) self.assertEquals(graph[0, 0], 1) self.assertEquals(graph[3, 5], 0.1) self.assertEquals(graph[2, 2], 1) self.assertEquals(graph.getNumEdges(), 3) self.assertEquals(graph.getNumVertices(), numVertices) self.assertEquals(graph.isUndirected(), True) for i in range(numVertices): nptst.assert_array_equal(graph.getVertex(i), newGraph.getVertex(i))
def profileSimulate(self): startDate, endDate, recordStep, printStep, M, targetGraph = HIVModelUtils.realSimulationParams() meanTheta, sigmaTheta = HIVModelUtils.estimatedRealTheta() meanTheta = numpy.array([337, 1.4319, 0.211, 0.0048, 0.0032, 0.5229, 0.042, 0.0281, 0.0076, 0.0293]) undirected = True graph = HIVGraph(M, undirected) logging.info("Created graph: " + str(graph)) alpha = 2 zeroVal = 0.9 p = Util.powerLawProbs(alpha, zeroVal) hiddenDegSeq = Util.randomChoice(p, graph.getNumVertices()) rates = HIVRates(graph, hiddenDegSeq) model = HIVEpidemicModel(graph, rates) model.setT0(startDate) model.setT(startDate+100) model.setRecordStep(recordStep) model.setPrintStep(printStep) model.setParams(meanTheta) logging.debug("MeanTheta=" + str(meanTheta)) ProfileUtils.profile('model.simulate()', globals(), locals())
def testInfectionProbability(self): undirected = True numVertices = 10 graph = HIVGraph(numVertices, undirected) hiddenDegSeq = self.gen.rvs(size=graph.getNumVertices()) rates = HIVRates(graph, hiddenDegSeq) t = 0.1 graph.getVertex(0)[HIVVertices.stateIndex] = HIVVertices.infected graph.getVertex(1)[HIVVertices.stateIndex] = HIVVertices.removed graph.getVertex(2)[HIVVertices.stateIndex] = HIVVertices.infected for vertexInd1 in range(numVertices): for vertexInd2 in range(numVertices): vertex1 = graph.getVertex(vertexInd1) vertex2 = graph.getVertex(vertexInd2) if vertex1[HIVVertices.stateIndex]!=HIVVertices.infected or vertex2[HIVVertices.stateIndex]!=HIVVertices.susceptible: self.assertEquals(rates.infectionProbability(vertexInd1, vertexInd2, t), 0.0) elif vertex1[HIVVertices.genderIndex] == HIVVertices.female and vertex2[HIVVertices.genderIndex] == HIVVertices.male: self.assertEquals(rates.infectionProbability(vertexInd1, vertexInd2, t), rates.infectProb) elif vertex1[HIVVertices.genderIndex] == HIVVertices.male and vertex2[HIVVertices.genderIndex] == HIVVertices.female: self.assertEquals(rates.infectionProbability(vertexInd1, vertexInd2, t), rates.infectProb) elif vertex1[HIVVertices.genderIndex] == HIVVertices.male and vertex2[HIVVertices.orientationIndex]==HIVVertices.bi: self.assertEquals(rates.infectionProbability(vertexInd1, vertexInd2, t), rates.infectProb) else: self.assertEquals(rates.infectionProbability(vertexInd1, vertexInd2, t), 0.0)
def testRemoveEvent(self): undirected = True numVertices = 10 graph = HIVGraph(numVertices, undirected) hiddenDegSeq = self.gen.rvs(size=graph.getNumVertices()) rates = HIVRates(graph, hiddenDegSeq) t = 0.1 V = graph.getVertexList().getVertices() femaleInds = V[:, HIVVertices.genderIndex]==HIVVertices.female maleInds = V[:, HIVVertices.genderIndex]==HIVVertices.male biMaleInds = numpy.logical_and(maleInds, V[:, HIVVertices.orientationIndex]==HIVVertices.bi) self.assertEquals(rates.expandedDegSeqFemales.shape[0], hiddenDegSeq[femaleInds].sum()*rates.p) self.assertEquals(rates.expandedDegSeqMales.shape[0], hiddenDegSeq[maleInds].sum()*rates.p) self.assertEquals(rates.expandedDegSeqBiMales.shape[0], hiddenDegSeq[biMaleInds].sum()*rates.p) graph.getVertexList().setInfected(4, t) graph.getVertexList().setInfected(7, t) graph.getVertexList().setInfected(8, t) rates.removeEvent(4, HIVVertices.randomDetect, t) rates.removeEvent(7, HIVVertices.randomDetect, t) removedInds= list(graph.getRemovedSet()) hiddenDegSeq[removedInds] = 0 #Check the new degree sequences are correct self.assertEquals(rates.expandedDegSeqFemales.shape[0], hiddenDegSeq[femaleInds].sum()*rates.p) self.assertEquals(rates.expandedDegSeqMales.shape[0], hiddenDegSeq[maleInds].sum()*rates.p) self.assertEquals(rates.expandedDegSeqBiMales.shape[0], hiddenDegSeq[biMaleInds].sum()*rates.p)
def createModel(t): """ The parameter t is the particle index. """ undirected = True graph = HIVGraph(M, undirected) alpha = 2 zeroVal = 0.9 p = Util.powerLawProbs(alpha, zeroVal) hiddenDegSeq = Util.randomChoice(p, graph.getNumVertices()) featureInds= numpy.ones(graph.vlist.getNumFeatures(), numpy.bool) featureInds[HIVVertices.dobIndex] = False featureInds[HIVVertices.infectionTimeIndex] = False featureInds[HIVVertices.hiddenDegreeIndex] = False featureInds[HIVVertices.stateIndex] = False featureInds = numpy.arange(featureInds.shape[0])[featureInds] matcher = GraphMatch("PATH", alpha=0.5, featureInds=featureInds, useWeightM=False) graphMetrics = HIVGraphMetrics2(targetGraph, breakDist, matcher, endDate) graphMetrics.breakDist = 0.0 rates = HIVRates(graph, hiddenDegSeq) model = HIVEpidemicModel(graph, rates, T=float(endDate), T0=float(startDate), metrics=graphMetrics) model.setRecordStep(recordStep) return model
def testContactRates(self): undirected = True numVertices = 10 graph = HIVGraph(numVertices, undirected) t = 0.2 contactList = range(numVertices) hiddenDegSeq = self.gen.rvs(size=graph.getNumVertices()) rates = HIVRates(graph, hiddenDegSeq) contactRateInds, contactRates = rates.contactRates([0, 5, 7], contactList, t) self.assertEquals(contactRates.shape[0], 3) #Now we have that 0 had contact with another rates.contactEvent(0, 3, 0.2) rates.contactEvent(1, 9, 0.1) infectedInds = numpy.arange(numVertices) contactRateInds, contactRates = rates.contactRates(infectedInds, contactList, t) #Note that in some cases an infected has no contacted as the persons do not match for i in range(infectedInds.shape[0]): if contactRateInds[i] != -1: if graph.getVertex(infectedInds[i])[HIVVertices.genderIndex]==graph.getVertex(contactRateInds[i])[HIVVertices.genderIndex]: self.assertEquals(contactRates[i], rates.heteroContactRate) elif graph.getVertex(infectedInds[i])[HIVVertices.genderIndex]!=graph.getVertex(contactRateInds[1])[HIVVertices.genderIndex] and graph.getVertex(infectedInds[i])[HIVVertices.orientationIndex]==HIVVertices.bi and graph.getVertex(contactRateInds[i])[HIVVertices.orientationIndex]==HIVVertices.bi: self.assertEquals(contactRates[i],rates.biContactRate)
def testContructor(self): numVertices = 10 graph = HIVGraph(numVertices) self.assertEquals(numVertices, graph.getNumVertices()) self.assertEquals(8, graph.getVertexList().getNumFeatures()) self.assertTrue(graph.isUndirected() == True)
def testRandomDetectionRates(self): undirected = True numVertices = 10 graph = HIVGraph(numVertices, undirected) t = 0.1 graph.getVertexList().setInfected(0, t) hiddenDegSeq = self.gen.rvs(size=graph.getNumVertices()) rates = HIVRates(graph, hiddenDegSeq) infectedList = [0, 2, 9] rdRates = rates.randomDetectionRates(infectedList, float(graph.size - len(graph.getRemovedSet()))) nptst.assert_array_almost_equal(rdRates, numpy.ones(len(infectedList))*rates.randDetectRate*len(infectedList)/float(graph.size - len(graph.getRemovedSet())))
def simulate(theta, startDate, endDate, recordStep, M, graphMetrics=None): undirected = True graph = HIVGraph(M, undirected) logging.debug("Created graph: " + str(graph)) alpha = 2 zeroVal = 0.9 p = Util.powerLawProbs(alpha, zeroVal) hiddenDegSeq = Util.randomChoice(p, graph.getNumVertices()) rates = HIVRates(graph, hiddenDegSeq) model = HIVEpidemicModel(graph, rates, endDate, startDate, metrics=graphMetrics) model.setRecordStep(recordStep) model.setParams(theta) logging.debug("Theta = " + str(theta)) return model.simulate(True)
def testContactEvent(self): undirected = True numVertices = 10 graph = HIVGraph(numVertices, undirected) #for i in range(numVertices): # logging.debug(graph.getVertex(i)) t = 0.2 hiddenDegSeq = self.gen.rvs(size=graph.getNumVertices()) rates = HIVRates(graph, hiddenDegSeq) V = graph.getVertexList().getVertices() femaleInds = V[:, HIVVertices.genderIndex]==HIVVertices.female maleInds = V[:, HIVVertices.genderIndex]==HIVVertices.male biMaleInds = numpy.logical_and(maleInds, V[:, HIVVertices.orientationIndex]==HIVVertices.bi) self.assertEquals(rates.expandedDegSeqFemales.shape[0], hiddenDegSeq[femaleInds].sum()*rates.p) self.assertEquals(rates.expandedDegSeqMales.shape[0], hiddenDegSeq[maleInds].sum()*rates.p) self.assertEquals(rates.expandedDegSeqBiMales.shape[0], hiddenDegSeq[biMaleInds].sum()*rates.p) for i in range(numVertices): self.assertEquals(rates.contactTimesArr[i], -1) rates.contactEvent(0, 9, 0.1) rates.contactEvent(0, 3, 0.2) self.assertEquals(graph.getEdge(0, 3), 0.2) self.assertEquals(graph.getEdge(0, 9), 0.1) self.assertTrue((rates.contactTimesArr[0] == numpy.array([3])).all()) self.assertTrue((rates.contactTimesArr[9] == numpy.array([0])).all()) self.assertTrue((rates.contactTimesArr[3] == numpy.array([0])).all()) for i in range(numVertices): self.assertTrue((rates.neighboursList[i] == graph.neighbours(i)).all()) #Check that the degree sequence is correct degSequence = graph.outDegreeSequence() r = rates.q-rates.p self.assertEquals(rates.expandedDegSeqFemales.shape[0], hiddenDegSeq[femaleInds].sum()*rates.p + degSequence[femaleInds].sum()*r) self.assertEquals(rates.expandedDegSeqMales.shape[0], hiddenDegSeq[maleInds].sum()*rates.p + degSequence[maleInds].sum()*r) self.assertEquals(rates.expandedDegSeqBiMales.shape[0], hiddenDegSeq[biMaleInds].sum()*rates.p + degSequence[biMaleInds].sum()*r)
def testContactRates3(self): #Figure out why infection does not explode when we set infection probability #to a high value and do not detect undirected = True numVertices = 20 graph = HIVGraph(numVertices, undirected) hiddenDegSeq = self.gen.rvs(size=graph.getNumVertices()) rates = HIVRates(graph, hiddenDegSeq) t = 0.1 for i in range(10): graph.getVertexList().setInfected(i, t) t = 0.2 infectedList = graph.infectedIndsAt(t) contactList = range(0, numVertices) contactRateInds, contactRates = rates.contactRates(infectedList, contactList, t) print(contactRateInds, contactRates)
def setUp(self): numpy.seterr(invalid='raise') logging.basicConfig(stream=sys.stdout, level=logging.DEBUG) numpy.set_printoptions(suppress=True, precision=4, linewidth=100) numpy.random.seed(21) M = 1000 undirected = True graph = HIVGraph(M, undirected) alpha = 2 zeroVal = 0.9 p = Util.powerLawProbs(alpha, zeroVal) hiddenDegSeq = Util.randomChoice(p, graph.getNumVertices()) rates = HIVRates(graph, hiddenDegSeq) self.numParams = 6 self.graph = graph self.meanTheta = numpy.array([100, 0.9, 0.05, 0.001, 0.1, 0.005]) self.hivAbcParams = HIVABCParameters(self.meanTheta, self.meanTheta/2)
def testUpperDetectionRates(self): """ See if the upper bound on detection rates is correct """ undirected = True numVertices = 10 graph = HIVGraph(numVertices, undirected) hiddenDegSeq = self.gen.rvs(size=graph.getNumVertices()) rates = HIVRates(graph, hiddenDegSeq) t = 0.1 graph.getVertexList().setInfected(0, t) graph.getVertexList().setInfected(1, t) graph.getVertexList().setInfected(8, t) t = 0.2 rates.removeEvent(8, HIVVertices.randomDetect, t) rates.infectionProbability = 1.0 infectedList = graph.infectedIndsAt(t) removedList = graph.removedIndsAt(t) n = graph.size-removedList self.assertEquals(rates.upperDetectionRates(infectedList, n), rates.randomDetectionRates(infectedList, n, seed=21).sum()) t = 0.3 rates.contactEvent(0, 2, t) graph.vlist.setInfected(2, t) t = 0.4 rates.removeEvent(0, HIVVertices.randomDetect, t) infectedList = graph.infectedIndsAt(t) removedSet = graph.removedIndsAt(t) removedSet = set(removedSet.tolist()) nptst.assert_array_almost_equal(rates.contactTracingRates(infectedList, removedSet, t + rates.ctStartTime + 1), numpy.array([0, rates.ctRatePerPerson])) upperDetectionRates = rates.ctRatePerPerson + rates.randomDetectionRates(infectedList, n, seed=21).sum() self.assertEquals(rates.upperDetectionRates(infectedList, n), upperDetectionRates)
def findDerivative(args): pertScale, startDate, endDate, recordStep, M, targetGraph, seed = args numpy.random.seed(seed) meanTheta, sigmaTheta = HIVModelUtils.toyTheta() epsilon = 5.0 undirected = True alpha = 2 zeroVal = 0.9 p = Util.powerLawProbs(alpha, zeroVal) graph = HIVGraph(M, undirected) featureInds= numpy.ones(graph.vlist.getNumFeatures(), numpy.bool) featureInds[HIVVertices.dobIndex] = False featureInds[HIVVertices.infectionTimeIndex] = False featureInds[HIVVertices.hiddenDegreeIndex] = False featureInds[HIVVertices.stateIndex] = False featureInds = numpy.arange(featureInds.shape[0])[featureInds] matcher = GraphMatch("PATH", alpha=0.5, featureInds=featureInds, useWeightM=False) abcParams = HIVABCParameters(meanTheta, sigmaTheta, pertScale) newTheta = abcParams.perturbationKernel(meanTheta) undirected = True graph = HIVGraph(M, undirected) graphMetrics = HIVGraphMetrics2(targetGraph, epsilon, matcher, float(endDate)) graphMetrics.breakDist = 1.0 hiddenDegSeq = Util.randomChoice(p, graph.getNumVertices()) rates = HIVRates(graph, hiddenDegSeq) model = HIVEpidemicModel(graph, rates, T=float(endDate), T0=float(startDate), metrics=graphMetrics) model.setRecordStep(recordStep) model.setParams(meanTheta) times, infectedIndices, removedIndices, graph = model.simulate(True) return abs(0.7 - graphMetrics.distance())/numpy.linalg.norm(newTheta-meanTheta)
def runModel(theta, endDate=100.0, M=1000): numpy.random.seed(21) undirected= True recordStep = 10 printStep = 10 startDate = 0 alpha = 2 zeroVal = 0.9 p = Util.powerLawProbs(alpha, zeroVal) graph = HIVGraph(M, undirected) hiddenDegSeq = Util.randomChoice(p, graph.getNumVertices()) logging.debug("MeanTheta=" + str(theta)) rates = HIVRates(graph, hiddenDegSeq) model = HIVEpidemicModel(graph, rates, endDate, startDate) model.setRecordStep(recordStep) model.setPrintStep(printStep) model.setParams(theta) times, infectedIndices, removedIndices, graph = model.simulate(True) return times, infectedIndices, removedIndices, graph, model
class HIVRatesProfile(): def __init__(self): #Total number of people in population self.M = 10000 numInitialInfected = 5 #The graph is one in which edges represent a contact undirected = True self.graph = HIVGraph(self.M, undirected) for i in range(self.M): vertex = self.graph.getVertex(i) #Set the infection time of a number of individuals to 0 if i < numInitialInfected: vertex[HIVVertices.stateIndex] = HIVVertices.infected outputDirectory = PathDefaults.getOutputDir() directory = outputDirectory + "test/" self.profileFileName = directory + "profile.cprof" def profileContactRate(self): susceptibleList = list(range(1, self.graph.getNumVertices())) t = 10 s = 3 gen = scipy.stats.zipf(s) hiddenDegSeq = gen.rvs(size=self.graph.getNumVertices()) rates = HIVRates(self.graph, hiddenDegSeq) numContactEvents = 5000 for i in range(numContactEvents): vertexInd1 = numpy.random.randint(0, self.graph.getNumVertices()) vertexInd2 = numpy.random.randint(0, self.graph.getNumVertices()) rates.contactEvent(vertexInd1, vertexInd2, 5) print((self.graph.getNumEdges())) infectedList = range(0, 100) contactList = range(100, self.M) t = 10 def runContactRates(): for i in range(100): rates.contactRates(infectedList, contactList, t) ProfileUtils.profile('runContactRates()', globals(), locals()) def profileInfectionProbability(self): s = 3 gen = scipy.stats.zipf(s) hiddenDegSeq = gen.rvs(size=self.graph.getNumVertices()) rates = HIVRates(self.graph, hiddenDegSeq) t = 5 #Getting vertices and checking parameters takes the most time def runInfectionProbs(): for i in range(10000): vertexInd1 = numpy.random.randint(0, self.graph.getNumVertices()) vertexInd2 = numpy.random.randint(0, self.graph.getNumVertices()) rates.infectionProbability(vertexInd1, vertexInd2, t) ProfileUtils.profile('runInfectionProbs()', globals(), locals()) def profileContactTracingRate(self): s = 3 gen = scipy.stats.zipf(s) hiddenDegSeq = gen.rvs(size=self.graph.getNumVertices()) rates = HIVRates(self.graph, hiddenDegSeq) #Create a network of sexual contacts numContactEvents = 10000 for i in range(numContactEvents): vertexInd1 = numpy.random.randint(0, self.graph.getNumVertices()) vertexInd2 = numpy.random.randint(0, self.graph.getNumVertices()) rates.contactEvent(vertexInd1, vertexInd2, 5) print((self.graph)) print((self.graph.degreeDistribution())) #Choose some individuals as being infected and then detected p = 0.3 q = 0.4 for i in range(self.graph.getNumVertices()): if numpy.random.rand() < p and not self.graph.getVertex(i)[HIVVertices.stateIndex] == HIVVertices.infected: self.graph.getVertexList().setInfected(i, 5.0) if numpy.random.rand() < q: self.graph.getVertexList().setDetected(i, 6.0, HIVVertices.randomDetect) infectedSet = self.graph.getInfectedSet() print((len(infectedSet))) print((len(self.graph.getRemovedSet()))) removedSet = self.graph.getRemovedSet() t = 200 def runContactTracingRate(): for j in range(2000): rates.contactTracingRates(list(infectedSet), removedSet, t) ProfileUtils.profile('runContactTracingRate()', globals(), locals())
def testContactTracingRate(self): undirected = True numVertices = 10 graph = HIVGraph(numVertices, undirected) hiddenDegSeq = self.gen.rvs(size=graph.getNumVertices()) rates = HIVRates(graph, hiddenDegSeq) t = 0.1 graph.getVertexList().setInfected(0, t) rates.contactEvent(0, 3, 0.2) rates.contactEvent(0, 9, 0.1) t = 0.3 graph.getVertexList().setInfected(3, t) graph.getVertexList().setInfected(9, t) t = 0.4 rates.removeEvent(0, HIVVertices.randomDetect, t) removedSet = graph.getRemovedSet() infectedList = [3, 9] ctRates = rates.contactTracingRates(infectedList, removedSet, t) self.assertTrue((ctRates==numpy.array([0.0, 0.0])).all()) ctRates = rates.contactTracingRates(infectedList, removedSet, t+rates.ctStartTime) self.assertTrue((ctRates == numpy.array([rates.ctRatePerPerson, rates.ctRatePerPerson])).all()) #Test contact tracing is within correct time period ctRates = rates.contactTracingRates(infectedList, removedSet, t+rates.ctEndTime-0.01) self.assertTrue((ctRates == numpy.array([rates.ctRatePerPerson, rates.ctRatePerPerson])).all()) ctRates = rates.contactTracingRates(infectedList, removedSet, t+rates.ctEndTime+1) self.assertTrue((ctRates == numpy.array([0, 0])).all()) rates.contactEvent(3, 5, t) graph.getVertexList().setInfected(5, t) rates.removeEvent(5, HIVVertices.randomDetect, t) removedSet = graph.getRemovedSet() ctRates = rates.contactTracingRates(infectedList, removedSet, t+rates.ctStartTime) self.assertTrue((ctRates == numpy.array([rates.ctRatePerPerson, rates.ctRatePerPerson])).all()) rates.contactEvent(3, 6, t) graph.getVertexList().setInfected(6, t) infectedList = [3, 6, 9] removedSet = graph.getRemovedSet() ctRates = rates.contactTracingRates(infectedList, removedSet, t+rates.ctStartTime) self.assertTrue((ctRates == numpy.array([rates.ctRatePerPerson, 0, rates.ctRatePerPerson])).all()) #Now make removedSet bigger than infectedList graph.getVertexList().setInfected(4, t) graph.getVertexList().setInfected(7, t) graph.getVertexList().setInfected(8, t) graph.getVertexList().setDetected(4, t, HIVVertices.randomDetect) graph.getVertexList().setDetected(7, t, HIVVertices.randomDetect) graph.getVertexList().setDetected(8, t, HIVVertices.randomDetect) #Note: InfectedList is out of order infectedList = list(graph.getInfectedSet()) sortInds = numpy.argsort(numpy.array(infectedList)) removedSet = graph.getRemovedSet() ctRates = rates.contactTracingRates(infectedList, removedSet, t+rates.ctStartTime) ctRates2 = numpy.array([rates.ctRatePerPerson, 0, rates.ctRatePerPerson]) self.assertTrue((ctRates[sortInds] == ctRates2).all()) #Test the case where InfectedList is out of order and removedSet is small graph.getVertexList().setInfected(4, t) graph.getVertex(7)[HIVVertices.stateIndex] = HIVVertices.susceptible graph.getVertex(8)[HIVVertices.stateIndex] = HIVVertices.susceptible infectedList = list(graph.getInfectedSet()) sortInds = numpy.argsort(numpy.array(infectedList)) removedSet = graph.getRemovedSet() ctRates = rates.contactTracingRates(infectedList, removedSet, t+rates.ctStartTime) ctRates2 = numpy.array([rates.ctRatePerPerson, 0, 0, rates.ctRatePerPerson]) self.assertTrue((ctRates[sortInds] == ctRates2).all())
def testContactRates2(self): undirected = True numVertices = 10 graph = HIVGraph(numVertices, undirected) maleVertex = graph.getVertex(0) maleVertex[HIVVertices.genderIndex] = HIVVertices.male femaleVertex = maleVertex.copy() femaleVertex[HIVVertices.genderIndex] = HIVVertices.female for i in range(5): graph.setVertex(i, maleVertex) graph.setVertex(i+5, femaleVertex) V = graph.getVertexList().getVertices() contactList = range(numVertices) #Test that the parameters alpha and C do the right thing hiddenDegSeq = self.gen.rvs(size=graph.getNumVertices()) rates = HIVRates(graph, hiddenDegSeq) t = 0.2 logging.debug("Rates with no existing contacts") contactRateInds, contactRates = rates.contactRates(range(numVertices), contactList, t) #When there are no contacts the choice is easy and some random new contacts #are chosen. #Now test differences in choice between existing and new contact. t = 0.3 for i in range(5): rates.contactEvent(i, i+5, t) rates.alpha = 1.0 logging.debug("Rates with default alpha=" + str(rates.alpha)) contactRateInds, contactRates = rates.contactRates(range(numVertices), contactList, 0.4) for i in range(5): self.assertTrue(contactRates[i] == rates.contactRate) self.assertTrue(contactRateInds[i] == i+5) #Now try changing alpha logging.debug("Rates with alpha=0.5") rates.setAlpha(0.5) contactRateInds, contactRates = rates.contactRates(range(numVertices), contactList, 0.4) #Observed probabilities change as expected #Now increase time and observe probabilities logging.debug("Rates with t=20") contactRateInds, contactRates = rates.contactRates(range(numVertices), contactList, 20) #Test we don't pick from removed graph.getVertexList().setInfected(0, t) graph.getVertexList().setInfected(4, t) graph.getVertexList().setInfected(7, t) graph.getVertexList().setInfected(8, t) #graph.getVertexList().setDetected(4, t, HIVVertices.randomDetect) #graph.getVertexList().setDetected(7, t, HIVVertices.randomDetect) rates.removeEvent(4, HIVVertices.randomDetect, t) rates.removeEvent(7, HIVVertices.randomDetect, t) infectedSet = graph.getInfectedSet() susceptibleSet = graph.getSusceptibleSet() removedSet = graph.getRemovedSet() contactSet = infectedSet.union(susceptibleSet) infectedList = list(infectedSet) removedList = list(removedSet) contactList = list(contactSet) contactRateInds, contactRates = rates.contactRates(infectedList, contactList, 20) #Contacts cannot be in removed set self.assertTrue(numpy.intersect1d(contactRateInds, numpy.array(removedList)).shape[0]==0)
numpy.set_printoptions(suppress=True, precision=4, linewidth=100) startDate, endDate, recordStep, M, targetGraph = HIVModelUtils.realSimulationParams() endDate = startDate + 10000 meanTheta, sigmaTheta = HIVModelUtils.estimatedRealTheta() meanTheta = numpy.array([ 50, 0.5131, 0.3242, 0.1, 0.0001, 0.0, 325, 0.34, 0.001, 0.1, 0.1, 0.1]) outputDir = PathDefaults.getOutputDir() + "viroscopy/" undirected = True graph = HIVGraph(M, undirected) logging.info("Created graph: " + str(graph)) alpha = 2 zeroVal = 0.9 p = Util.powerLawProbs(alpha, zeroVal) hiddenDegSeq = Util.randomChoice(p, graph.getNumVertices()) rates = HIVRates(graph, hiddenDegSeq) model = HIVEpidemicModel(graph, rates) model.setT0(startDate) model.setT(endDate) model.setRecordStep(recordStep) model.setParams(meanTheta) logging.debug("MeanTheta=" + str(meanTheta)) times, infectedIndices, removedIndices, graph = model.simulate(True) times, vertexArray, removedGraphStats = HIVModelUtils.generateStatistics(graph, startDate, endDate, recordStep) plt.figure(0)
def testSimulate2(self): startDate = 0.0 endDate = 100.0 M = 1000 meanTheta, sigmaTheta = HIVModelUtils.estimatedRealTheta() undirected = True graph = HIVGraph(M, undirected) alpha = 2 zeroVal = 0.9 p = Util.powerLawProbs(alpha, zeroVal) hiddenDegSeq = Util.randomChoice(p, graph.getNumVertices()) meanTheta[4] = 0.1 recordStep = 10 printStep = 10 rates = HIVRates(graph, hiddenDegSeq) model = HIVEpidemicModel(graph, rates, endDate, startDate) model.setRecordStep(recordStep) model.setPrintStep(printStep) model.setParams(meanTheta) initialInfected = graph.getInfectedSet() times, infectedIndices, removedIndices, graph = model.simulate(True) #Now test the final graph edges = graph.getAllEdges() for i, j in edges: if graph.vlist.V[i, HIVVertices.genderIndex] == graph.vlist.V[j, HIVVertices.genderIndex] and (graph.vlist.V[i, HIVVertices.orientationIndex] != HIVVertices.bi or graph.vlist.V[j, HIVVertices.orientationIndex] != HIVVertices.bi): self.fail() finalInfected = graph.getInfectedSet() finalRemoved = graph.getRemovedSet() self.assertEquals(numpy.intersect1d(initialInfected, finalRemoved).shape[0], len(initialInfected)) #Test case where there is no contact meanTheta = numpy.array([100, 0.95, 1, 1, 0, 0, 0, 0, 0, 0, 0], numpy.float) times, infectedIndices, removedIndices, graph, model = runModel(meanTheta) self.assertEquals(len(graph.getInfectedSet()), 100) self.assertEquals(len(graph.getRemovedSet()), 0) self.assertEquals(graph.getNumEdges(), 0) heteroContactRate = 0.1 meanTheta = numpy.array([100, 0.95, 1, 1, 0, 0, heteroContactRate, 0, 0, 0, 0], numpy.float) times, infectedIndices, removedIndices, graph, model = runModel(meanTheta) self.assertEquals(len(graph.getInfectedSet()), 100) self.assertEquals(len(graph.getRemovedSet()), 0) edges = graph.getAllEdges() for i, j in edges: self.assertNotEqual(graph.vlist.V[i, HIVVertices.genderIndex], graph.vlist.V[j, HIVVertices.genderIndex]) #Number of conacts = rate*people*time infectedSet = graph.getInfectedSet() numHetero = (graph.vlist.V[list(infectedSet), HIVVertices.orientationIndex] == HIVVertices.hetero).sum() self.assertTrue(abs(numHetero*endDate*heteroContactRate- model.getNumContacts()) < 100) heteroContactRate = 0.01 meanTheta = numpy.array([100, 0.95, 1, 1, 0, 0, heteroContactRate, 0, 0, 0, 0], numpy.float) times, infectedIndices, removedIndices, graph, model = runModel(meanTheta) infectedSet = graph.getInfectedSet() numHetero = (graph.vlist.V[list(infectedSet), HIVVertices.orientationIndex] == HIVVertices.hetero).sum() self.assertAlmostEqual(numHetero*endDate*heteroContactRate/100, model.getNumContacts()/100.0, 0)
class HIVEpidemicModelTest(unittest.TestCase): def setUp(self): numpy.random.seed(21) numpy.set_printoptions(suppress=True, precision=4) logging.basicConfig(stream=sys.stdout, level=logging.DEBUG) M = 100 undirected = True self.graph = HIVGraph(M, undirected) s = 3 self.gen = scipy.stats.zipf(s) hiddenDegSeq = self.gen.rvs(size=self.graph.getNumVertices()) rates = HIVRates(self.graph, hiddenDegSeq) self.model = HIVEpidemicModel(self.graph, rates) def testSimulate(self): T = 1.0 self.graph.getVertexList().setInfected(0, 0.0) self.model.setT(T) times, infectedIndices, removedIndices, graph = self.model.simulate(verboseOut=True) numInfects = 0 for i in range(graph.getNumVertices()): if graph.getVertex(i)[HIVVertices.stateIndex] == HIVVertices==infected: numInfects += 1 self.assertTrue(numInfects == 0 or times[len(times)-1] >= T) #Test with a larger population as there seems to be an error when the #number of infectives becomes zero. M = 100 undirected = True graph = HIVGraph(M, undirected) graph.setRandomInfected(10, 0.95) self.graph.removeAllEdges() T = 21.0 hiddenDegSeq = self.gen.rvs(size=self.graph.getNumVertices()) rates = HIVRates(self.graph, hiddenDegSeq) model = HIVEpidemicModel(self.graph, rates) model.setRecordStep(10) model.setT(T) times, infectedIndices, removedIndices, graph = model.simulate(verboseOut=True) self.assertTrue((times == numpy.array([0, 10, 20], numpy.int)).all()) self.assertEquals(len(infectedIndices), 3) self.assertEquals(len(removedIndices), 3) #TODO: Much better testing def testSimulate2(self): startDate = 0.0 endDate = 100.0 M = 1000 meanTheta, sigmaTheta = HIVModelUtils.estimatedRealTheta() undirected = True graph = HIVGraph(M, undirected) alpha = 2 zeroVal = 0.9 p = Util.powerLawProbs(alpha, zeroVal) hiddenDegSeq = Util.randomChoice(p, graph.getNumVertices()) meanTheta[4] = 0.1 recordStep = 10 printStep = 10 rates = HIVRates(graph, hiddenDegSeq) model = HIVEpidemicModel(graph, rates, endDate, startDate) model.setRecordStep(recordStep) model.setPrintStep(printStep) model.setParams(meanTheta) initialInfected = graph.getInfectedSet() times, infectedIndices, removedIndices, graph = model.simulate(True) #Now test the final graph edges = graph.getAllEdges() for i, j in edges: if graph.vlist.V[i, HIVVertices.genderIndex] == graph.vlist.V[j, HIVVertices.genderIndex] and (graph.vlist.V[i, HIVVertices.orientationIndex] != HIVVertices.bi or graph.vlist.V[j, HIVVertices.orientationIndex] != HIVVertices.bi): self.fail() finalInfected = graph.getInfectedSet() finalRemoved = graph.getRemovedSet() self.assertEquals(numpy.intersect1d(initialInfected, finalRemoved).shape[0], len(initialInfected)) #Test case where there is no contact meanTheta = numpy.array([100, 0.95, 1, 1, 0, 0, 0, 0, 0, 0, 0], numpy.float) times, infectedIndices, removedIndices, graph, model = runModel(meanTheta) self.assertEquals(len(graph.getInfectedSet()), 100) self.assertEquals(len(graph.getRemovedSet()), 0) self.assertEquals(graph.getNumEdges(), 0) heteroContactRate = 0.1 meanTheta = numpy.array([100, 0.95, 1, 1, 0, 0, heteroContactRate, 0, 0, 0, 0], numpy.float) times, infectedIndices, removedIndices, graph, model = runModel(meanTheta) self.assertEquals(len(graph.getInfectedSet()), 100) self.assertEquals(len(graph.getRemovedSet()), 0) edges = graph.getAllEdges() for i, j in edges: self.assertNotEqual(graph.vlist.V[i, HIVVertices.genderIndex], graph.vlist.V[j, HIVVertices.genderIndex]) #Number of conacts = rate*people*time infectedSet = graph.getInfectedSet() numHetero = (graph.vlist.V[list(infectedSet), HIVVertices.orientationIndex] == HIVVertices.hetero).sum() self.assertTrue(abs(numHetero*endDate*heteroContactRate- model.getNumContacts()) < 100) heteroContactRate = 0.01 meanTheta = numpy.array([100, 0.95, 1, 1, 0, 0, heteroContactRate, 0, 0, 0, 0], numpy.float) times, infectedIndices, removedIndices, graph, model = runModel(meanTheta) infectedSet = graph.getInfectedSet() numHetero = (graph.vlist.V[list(infectedSet), HIVVertices.orientationIndex] == HIVVertices.hetero).sum() self.assertAlmostEqual(numHetero*endDate*heteroContactRate/100, model.getNumContacts()/100.0, 0) def testSimulateBis(self): #Play with bi rate biContactRate = 0.1 endDate = 100.0 meanTheta = numpy.array([200, 0.95, 1, 1, 0, 0, 0, biContactRate, 0, 0, 0], numpy.float) times, infectedIndices, removedIndices, graph, model = runModel(meanTheta, endDate=endDate) infectedSet = graph.getInfectedSet() numBi = (graph.vlist.V[list(infectedSet), HIVVertices.orientationIndex] == HIVVertices.bi).sum() susceptibleSet = graph.getSusceptibleSet() self.assertTrue(abs(numBi*endDate*biContactRate- model.getNumContacts()) < 10) numContacts = model.getNumContacts() edges = graph.getAllEdges() numMSM = 0 for i, j in edges: self.assertTrue(graph.vlist.V[i, HIVVertices.orientationIndex]==HIVVertices.bi or graph.vlist.V[j, HIVVertices.orientationIndex]==HIVVertices.bi) if graph.vlist.V[i, HIVVertices.genderIndex] == graph.vlist.V[j, HIVVertices.genderIndex] and graph.vlist.V[i, HIVVertices.genderIndex]==HIVVertices.male: numMSM += 1 biContactRate = 0.2 meanTheta = numpy.array([200, 0.95, 1, 1, 0, 0, 0, biContactRate, 0, 0, 0], numpy.float) times, infectedIndices, removedIndices, graph, model = runModel(meanTheta) infectedSet = graph.getInfectedSet() numBi = (graph.vlist.V[list(infectedSet), HIVVertices.orientationIndex] == HIVVertices.bi).sum() numContacts2 = model.getNumContacts() self.assertTrue(abs(numContacts*2-numContacts2) < 15) #Try infection between men only biContactRate = 0.2 manBiInfectProb = 1.0 meanTheta = numpy.array([300, 0.95, 1, 1, 0, 0, 0, biContactRate, 0, 0, manBiInfectProb], numpy.float) times, infectedIndices, removedIndices, graph, model = runModel(meanTheta) #print(numpy.logical_and(graph.vlist.V[:, HIVVertices.orientationIndex] == HIVVertices.bi, graph.vlist.V[:, HIVVertices.genderIndex] == HIVVertices.male).sum()) newInfects = numpy.setdiff1d(graph.getInfectedSet(), numpy.array(infectedIndices[0])) self.assertTrue((graph.vlist.V[newInfects, HIVVertices.orientationIndex] == HIVVertices.bi).all()) self.assertTrue((graph.vlist.V[newInfects, HIVVertices.genderIndex] == HIVVertices.male).all()) def testSimulateInfects(self): #Test varying infection probabilities heteroContactRate = 0.1 manWomanInfectProb = 1.0 meanTheta = numpy.array([100, 0.95, 1, 1, 0, 0, heteroContactRate, 0, 0, manWomanInfectProb, 0], numpy.float) times, infectedIndices, removedIndices, graph, model = runModel(meanTheta) newInfects = numpy.setdiff1d(graph.getInfectedSet(), numpy.array(infectedIndices[0])) self.assertTrue((graph.vlist.V[newInfects, HIVVertices.genderIndex] == HIVVertices.female).all()) manWomanInfectProb = 0.1 meanTheta = numpy.array([100, 0.95, 1, 1, 0, 0, heteroContactRate, 0, 0, manWomanInfectProb, 0], numpy.float) times, infectedIndices, removedIndices, graph, model = runModel(meanTheta) newInfects2 = numpy.setdiff1d(graph.getInfectedSet(), numpy.array(infectedIndices[0])) self.assertTrue((graph.vlist.V[newInfects2, HIVVertices.genderIndex] == HIVVertices.female).all()) self.assertTrue(newInfects.shape[0] > newInfects2.shape[0]) #Now only women infect heteroContactRate = 0.1 womanManInfectProb = 1.0 meanTheta = numpy.array([100, 0.95, 1, 1, 0, 0, heteroContactRate, 0, womanManInfectProb, 0, 0], numpy.float) times, infectedIndices, removedIndices, graph, model = runModel(meanTheta) newInfects = numpy.setdiff1d(graph.getInfectedSet(), numpy.array(infectedIndices[0])) self.assertTrue((graph.vlist.V[newInfects, HIVVertices.genderIndex] == HIVVertices.male).all()) womanManInfectProb = 0.1 meanTheta = numpy.array([100, 0.95, 1, 1, 0, 0, heteroContactRate, 0, womanManInfectProb, 0, 0], numpy.float) times, infectedIndices, removedIndices, graph, model = runModel(meanTheta) newInfects2 = numpy.setdiff1d(graph.getInfectedSet(), numpy.array(infectedIndices[0])) self.assertTrue((graph.vlist.V[newInfects2, HIVVertices.genderIndex] == HIVVertices.male).all()) self.assertTrue(newInfects.shape[0] > newInfects2.shape[0]) def testSimulateDetects(self): heteroContactRate = 0.05 endDate = 100 randDetectRate = 0 meanTheta = numpy.array([100, 0.95, 1, 1, randDetectRate, 0, heteroContactRate, 0, 0, 0, 0], numpy.float) times, infectedIndices, removedIndices, graph, model = runModel(meanTheta) detectedSet = graph.getRemovedSet() self.assertEquals(len(detectedSet), 0) heteroContactRate = 0.0 randDetectRate = 0.01 meanTheta = numpy.array([100, 0.95, 1, 1, randDetectRate, 0, heteroContactRate, 0, 0, 0, 0], numpy.float) times, infectedIndices, removedIndices, graph, model = runModel(meanTheta) detectedSet = graph.getRemovedSet() self.assertTrue(len(detectedSet) < 100*randDetectRate*endDate) randDetectRate = 0.005 meanTheta = numpy.array([100, 0.95, 1, 1, randDetectRate, 0, heteroContactRate, 0, 0, 0, 0], numpy.float) times, infectedIndices, removedIndices, graph, model = runModel(meanTheta) detectedSet2 = graph.getRemovedSet() print(len(detectedSet), len(detectedSet2)) self.assertTrue(abs(len(detectedSet)*2 - len(detectedSet2))<15) removedGraph = graph.subgraph(list(graph.getRemovedSet())) edges = removedGraph.getAllEdges() for edge in edges: i, j = edge self.assertEquals(removedGraph.vlist.V[i, HIVVertices.detectionTimeIndex]. HIVVertices.randomDetect) self.assertEquals(removedGraph.vlist.V[j, HIVVertices.detectionTimeIndex]. HIVVertices.randomDetect) #Test contact tracing randDetectRate = 0 setCtRatePerPerson = 0.1 meanTheta = numpy.array([100, 0.95, 1, 1, randDetectRate, setCtRatePerPerson, heteroContactRate, 0, 0, 0, 0], numpy.float) times, infectedIndices, removedIndices, graph, model = runModel(meanTheta) detectedSet = graph.getRemovedSet() self.assertEquals(len(detectedSet), 0) randDetectRate = 0.001 setCtRatePerPerson = 0.1 meanTheta = numpy.array([100, 0.95, 1, 1, randDetectRate, setCtRatePerPerson, heteroContactRate, 0, 0, 0, 0], numpy.float) times, infectedIndices, removedIndices, graph, model = runModel(meanTheta, endDate=500.0) detectedSet = graph.getRemovedSet() removedGraph = graph.subgraph(list(graph.getRemovedSet())) edges = removedGraph.getAllEdges() for i in removedGraph.getAllVertexIds(): if removedGraph.vlist.V[i, HIVVertices.detectionTypeIndex] == HIVVertices.contactTrace: self.assertTrue(removedGraph.vlist.V[i, HIVVertices.detectionTimeIndex] >= 180) @unittest.skip("") def testFindStandardResults(self): times = [3, 12, 22, 25, 40, 50] infectedIndices = [[1], [1, 2], [1, 2], [1, 2], [1, 2], [1, 2]] removedIndices = [[1], [1, 2], [1, 2], [1, 2], [1, 2], [1, 2]] self.model.setT(51.0) self.model.setRecordStep(10) times, infectedIndices, removedIndices = self.model.findStandardResults(times, infectedIndices, removedIndices) self.assertTrue((numpy.array(times)==numpy.arange(0, 60, 10)).all()) #Now try case where simulation is slightly longer than T and infections = 0 numpy.random.seed(21) times = [3, 12, 22, 25, 40, 50] infectedIndices = [[1], [1, 2], [1, 2], [1, 2], [1, 2], [1, 2]] removedIndices = [[1], [1, 2], [1, 2], [1, 2], [1, 2], [1, 2]] self.model.setT(51.0) self.model.setRecordStep(10) times, infectedIndices, removedIndices = self.model.findStandardResults(times, infectedIndices, removedIndices) logging.debug(times)